Mining Geostatistics to Quantify the Spatial Variability of Certain Soil Flow Properties

Gerardo Severino, Maddalena Scarfato, Gerardo Toraldo
2016 Procedia Computer Science  
The functional dependence of the relative unsaturated hydraulic conductivity (UHC) K r (ψ) ≡ exp(αψ) upon the matric potential ψ, [L], via the soil-dependent parameter α, [L −1 ], has been traditionally regarded as a deterministic process (i.e. α ∼ constant). However, in the practical applications one is concerned with flow domains of large extents where α undergoes to significant spatial variations as consequence of the disordered soil's structure. To account for such a variability (hereafter
more » ... lso termed as "heterogeneity") we adopt the mining geostatistical approach, which regards α as a random space function (RSF). To quantify the heterogeneity of α, estimates of local-values were obtained from ∼ 100 locations along a trench where an internal drainage test was conducted. The analysis of the statistical moments of α demonstrates (in line with the current literature on the matter) that the log-transform ζ ≡ ln α can be regarded as a structureless, normally distributed, RSF. An novel implementation of the present study in the context of the "Internet of Things" (IoT) is outlined.
doi:10.1016/j.procs.2016.09.064 fatcat:s7dvdbheo5ezpo7umm2dbtnzxi